I think you would just need to replace the lm() function call with
cor(x,y,method="spearman". It would probably be more informative to
actually plot by the magnitude of the correlation coefficient (all |r| >=
0.20 or something similar) rather than just by those with P <=0.05.
Brian
Brian S. Cade, PhD
U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8818
email: ca...@usgs.gov <brian_c...@usgs.gov>
tel: 970 226-9326
On Thu, Apr 28, 2016 at 9:35 PM, Hoji, Akihiko <ak...@pitt.edu> wrote:
> Hi,
>
> A following function was kindly provided by GGally’s maintainer, Barret
> Schloerke.
>
> function(data, mapping, ...) {
> p <- ggplot(data = data, mapping = mapping) +
> geom_point(color = I("blue")) +
> geom_smooth(method = "lm", color = I("black"), ...) +
> theme_blank() +
> theme(panel.border=element_rect(fill=NA, linetype = "solid",
> color="black"))
>
> lmModel <- eval(substitute(lm(y ~ x, data = data), mapping))
> fs <- summary(lmModel)$fstatistic
> pValue <- pf(fs[1], fs[2], fs[3], lower.tail = FALSE)
>
> if (pValue < 0.05) {
> p <- p + theme(
> panel.border = element_rect(
> color = "red",
> size = 3,
> linetype = "solid",
> fill = "transparent"
> )
> )
> }
>
> p
> }
>
> Basically, this function draws red squares over pairwise corr plots with
> p<0.05. Now, since I need to use the spearman rank corr, I tried to modify
> the lm function by adding “method=spearman” but this did not work at al.
> Could anybody suggest the way to add the spearman rank corr function in
> this particular function ?
>
> Thanks.
>
>
>
>
>
> ______________________________________________
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